Heart Disease Prediction Classification using Machine Learning

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Shatendra Kumar Dubey
Dr. Sitesh Sinha
Dr. Anurag Jain

Abstract

Heart disease is a leading cause of mortality worldwide, and early detection and accurate prediction of heart disease can significantly improve patient outcomes. Machine learning techniques have shown great promise in assisting healthcare professionals in diagnosing and predicting heart disease. The diagnosis and prognosis of heart disease must be improved, refined, and accurate, because a small mistake can cause weakness or death. According to a recent World Health Organization study, 17.5 million people die each year. By 2030, this number will increase to 75 million.[2] This document explains how to enable online KSRM capabilities. The KSRM smart system allows users to report heart-related problems. This research paper aims to explore the use of machine learning algorithms for effective heart disease prediction classification with Adaboost for improve the accuracy of algorithm.

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[1]
Shatendra Kumar Dubey, Dr. Sitesh Sinha, and Dr. Anurag Jain , Trans., “Heart Disease Prediction Classification using Machine Learning”, IJIES, vol. 10, no. 11, pp. 1–6, Dec. 2023, doi: 10.35940/.
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How to Cite

[1]
Shatendra Kumar Dubey, Dr. Sitesh Sinha, and Dr. Anurag Jain , Trans., “Heart Disease Prediction Classification using Machine Learning”, IJIES, vol. 10, no. 11, pp. 1–6, Dec. 2023, doi: 10.35940/.
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